Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

DeepSeek

DeepSeek-R1

DeepSeek

DeepSeek-R1 is a language model developed by DeepSeek. It achieves strong performance with an average score of 74.1% across 20 benchmarks. It excels particularly in MATH-500 (97.3%), MMLU-Redux (92.9%), CLUEWSC (92.8%). It supports a 262K token context window for handling large documents. The model is available through 4 API providers. Released in 2025, it represents DeepSeek's latest advancement in AI technology.

Meta

Llama 3.2 11B Instruct

Meta

Llama 3.2 11B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 63.6% across 11 benchmarks. It excels particularly in AI2D (91.1%), DocVQA (88.4%), ChartQA (83.4%). It supports a 256K token context window for handling large documents. The model is available through 6 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Meta's latest advancement in AI technology.

Meta

Llama 3.2 11B Instruct

Meta

2024-09-25

DeepSeek

DeepSeek-R1

DeepSeek

2025-01-20

3 months newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-R1

Input:$0.55
Output:$2.19
Meta

Llama 3.2 11B Instruct

$2.64 cheaper
Input:$0.05
Output:$0.05

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-R1

Larger context
Max Context:262.1K
Parameters:671.0B
Meta

Llama 3.2 11B Instruct

Max Context:256.0K
Parameters:10.6B

Average performance across 2 common benchmarks

DeepSeek

DeepSeek-R1

+28.3%
Average Score:81.2%
Meta

Llama 3.2 11B Instruct

Average Score:52.9%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-R1

math
+39.9%
97.3%
general
+5.2%
75.3%
Meta

Llama 3.2 11B Instruct

math
57.4%
general
70.1%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Llama 3.2 11B Instruct

2023-12-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek

DeepSeek-R1

4 providers

Together

Throughput: 4 tok/s
Latency: 0.6ms

DeepInfra

Throughput: 0.9 tok/s
Latency: 0.3ms

Fireworks

Throughput: 2.1 tok/s
Latency: 0.3ms

DeepSeek

Throughput: 9 tok/s
Latency: 0.3ms
Meta

Llama 3.2 11B Instruct

6 providers

Sambanova

Throughput: 100 tok/s
Latency: 0.5ms

Together

Throughput: 168 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 108 tok/s
Latency: 0.5ms

Fireworks

Throughput: 125 tok/s
Latency: 0.2ms

Groq

Throughput: 100 tok/s
Latency: 0.5ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms
DeepSeek

DeepSeek-R1

+28.3%
Avg Score:81.2%
Providers:4
Meta

Llama 3.2 11B Instruct

Avg Score:52.9%
Providers:6